The present invention relates generally to detection of an orientation of a document image. More specifically, the present invention relates to automatic detection of an orientation of a binary image of a document including text and non-textual components.
Among the growing uses for computer systems include information databases and automation of data entry. Owners and users of paper-based documents are converting and storing information contained on the documents into electronic format for easy access through their computer systems. To assist in the conversion of paper-based information into electronic information suitable for quick searching and retrieval, document analysis systems process binary images of the documents.
A typical document analysis system includes scanning, displaying, quality assurance, image processing, text recognition, image and text database creation, and data retrieval processes. Efforts to improve the quality assurance and the text recognition processes include a desire to automatically determine an orientation of the individual pages. When printing text, a printer will typically output text in either portrait or landscape mode. It is important that a text recognition process know the orientation of text in a binary image before beginning the recognition operation. For automating the text recognition process, automatic detection of page orientation improves overall performance.
It is also important that automated data entry systems know an orientation of text in a binary image. Data entry systems include systems that process a binary image in order to separate out various components of the image, such as headline areas, text line areas, graphic areas, footnote areas, and background areas, for example.
Conventional page orientation systems employ orientation detection algorithms that have degraded performance when analyzing binary images that include significant non-textual elements. These non-textual elements can include graphics, forms, line art, large fonts, and dithered images, among other features. One reason conventional page orientation detection systems have degraded performance is due to their emphasis on global variations in characteristics of the binary image.